Building an Urban Mobility Dashboard with AI as Your Thought Partner
I wanted to share something cool I built this morning – an Urban Mobility Dashboard that helps city planners visualize and analyze mobility patterns using Google Maps. What’s even cooler? I built it in just 60 minutes with the help of Cursor AI!
About the Dashboard
The dashboard lets you:
- Select different cities (Vancouver, Madinah, Delhi, Lahore) or search for any location
- View simulated crowd density using heatmaps
- Analyze cultural sites and specific areas with interactive markers
- Compare day/night activity patterns
- View key mobility statistics like peak hours and estimated visitor counts
It’s built with Next.js, TypeScript, Tailwind CSS, and the Google Maps API – a modern stack that makes it responsive and user-friendly.
Read more: *Made with Cursor.com AI IDE* Urban Mobility Dashboard – Made in 60 min!How I Built It: The “Thought Partner” Approach
Here’s the real game-changer: I made a 12-minute video showing how I used Cursor (or any AI coding assistant) not just as a code generator, but as a true “thought partner” in development.
Instead of the typical approach of asking AI to fix small issues with individual prompts, I had an actual conversation with it to tackle bigger challenges. The key was prompting the AI to ask me questions and then answering those questions to guide the development process.
The first 2.5 minutes of my video showcase the finished app (which took just 60 minutes to build), while the remaining 10 minutes (condensed from 35-40 minutes of actual work) demonstrate the specific prompts and workflow I used.
Why This Approach Works
When you use AI as a thought partner:
- You can tackle complex projects much faster
- The AI helps you think through architecture decisions
- You avoid getting stuck on implementation details
- The back-and-forth conversation creates a more coherent codebase
Want to Try It?
Check out my GitHub repo at github.com/main-salman/mobility-dashboard to see the code and play with the app yourself!
The next time you’re starting a project, try treating your AI assistant as a thought partner rather than just a code generator. Ask it big-picture questions, let it suggest approaches, and have it ask you clarifying questions. You might be surprised at how much more productive you become!
Happy coding!
Salman Naqvi - 2xCCIE 